Abstract: A method and apparatus are described where account information is used to predict possible outcomes of a HELOC. To predict the possible outcomes, HELOC account state transition probabilities are modeled. The transition probabilities, determined by historic data regression analysis, provide the framework for a Monte Carlo simulation. The simulation is seeded with HELOC account information. A calculation engine takes the account information and simulates an elapse of time using a random number generator and the state transition probabilities. The simulation results in updated account information predicting a possible outcome over the elapsed time interval. The updated account information in turn may be used by the calculation engine to simulate the next elapse of time. This method may be iteratively repeated with the account information propagated forward until the end of the prediction period is reached.

Abstract: A method and apparatus are described where account information is used to predict possible outcomes of a HELOC. To predict the possible outcomes, HELOC account state transition probabilities are modeled. The transition probabilities, determined by historic data regression analysis, provide the framework for a Monte Carlo simulation. The simulation is seeded with HELOC account information. A calculation engine takes the account information and simulates an elapse of time using a random number generator and the state transition probabilities. The simulation results in updated account information predicting a possible outcome over the elapsed time interval. The updated account information in turn may be used by the calculation engine to simulate the next elapse of time. This method may be iteratively repeated with the account information propagated forward until the end of the prediction period is reached.